CN110458408A - Typical fault influences the analysis method of consequence on dynamic equipment and device - Google Patents
Typical fault influences the analysis method of consequence on dynamic equipment and device Download PDFInfo
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Abstract
The invention discloses typical faults to influence the analysis method of consequence on dynamic equipment and device, its be used for in refinery device dynamic equipment and the refinery device analyze, it is characterized in that, analysis of severity is carried out by consequence caused by the typical fault to dynamic equipment, the severity degree and different degree for obtaining the typical fault influence coefficient.With this analysis method, pass through the acquisition and analysis to related data, sequence severity analysis is carried out for the influence to the different degrees of typical fault of dynamic equipment all kinds of in device to equipment and device, the difference that the judgement of artificial subjectivity is converted into real data is embodied, enable the severity of failure to be more clear intuitively to be distinguished out, reliable data basis is provided for the analysis of subsequent device reliability, and the measures such as corresponding monitoring, replacement, maintenance, maintenance are in a planned way taken, guarantee that refinery device moves equipment safety reliability service.
Description
Technical field
The present invention relates to refinery device Analysis of Running Reliability fields.It is mainly used for moving device systems difference in refinery device
Influence of the typical fault of degree to equipment and device carries out sequence severity analysis.Sequence severity analysis is to design consequence
Severity score table, the sequence severity provided by enterprise related technical personnel according to practical work experience, then utilizes according to this
Analytic hierarchy process (AHP) and fuzzy multi factor evaluation method carry out analytical calculation, and by the analysis of this science, the judgement of artificial subjectivity is turned
The difference turned in real data embodies, and the severity of failure is made to be distinguished out clear and intuitively, basic herein
It is upper to improve the reliability assessment that equipment is moved to device, finally make corresponding dynamic Preventive Equipment Maintenance period, device overhaul
Period and maintenance policy.
Background technique
Refinery device is the oil refining processing unit (plant) using crude oil as raw material, and major product has: liquid hydrocarbon, naphtha or reformation
The raw materials such as material, diesel oil, hydrogenating materials, fcc raw material, coking and oxidized asphalt, therefore refinery device is referred to as petrochemical enterprise
Faucet device.Have in package unit largely dynamic equipment (mainly having fan for air cooler, pump and compressor) work together so that this
Set process flow can be realized completely, therefore the reliability for these dynamic equipment of analyzing and researching can to the steady safety of ensuring equipment
It is played a very important role by operation.
The core equipment that equipment is competition among enterprises is moved in petrochemical production equipment, its working efficiency directly influences enterprise
Production efficiency.The dynamic most power of equipment is big, revolving speed it is high structure is complicated, so being very easy to break down, and danger coefficient
Relatively high, it is because these dynamic equipment chance failures cause device to stop production that accident, which occurs, for some petroleum chemical enterprises all, and some is very
To producing the serious consequence such as explosion, hazardous materials spillage.Therefore it in order to ensure enterprise safety operation, studies in petrochemical equipment
The reliability of dynamic equipment has a very important significance.
With the appearance and continuous development of reliability engineering, maintenance (RCM) method centered on reliability is gradually pushed away
Wide and application.Application study by carrying out RCM method can understand the operating condition of dynamic equipment more fully hereinafter and make
The preventative maintenance scheme of effect, to ensure equipment even running.
It mainly includes the following aspects that general refinery device, which moves equipment and the reliability consideration work of system:
(1) fail-safe analysis is carried out to all kinds of dynamic equipment with RCM method, collects the operation with equipment dynamic in collating unit
With history maintenance record, calculates the moving law of corresponding dynamic equipment and formulate the suitable preventative maintenance period；
(2) serviceability block-scheme method and Bayesian network method carry out system reliability point to the dynamic device systems of device
Analysis.The process flow chart of coupling apparatus draws out corresponding system reliability block diagram and Bayesian network.It is calculated above-mentioned
Fail-safe analysis result substituted into two kinds of figures respectively and carry out analytical calculation, final the reliability trends for setting out device systems become
Law；
(3) system division is carried out to device according to related process process, counts the information for moving equipment in each system, and
Influence analysis of failure pattern (FMEA) analysis and risk assessment are carried out to the dynamic equipment in each system；
(4) the above analysis is combined, determine the preventative maintenance period of dynamic equipment and system and formulates corresponding maintenance plan
Slightly.
From the point of view of the above work, collecting with the operation of equipment dynamic in collating unit and history maintenance record is research work
Basis, and guarantee that subsequent fail-safe analysis and maintenance policy conclusion are correctly crucial.In order to guarantee data it is correct acquisition and
Analysis, it is necessary to which it is tight that the influence for the different degrees of typical fault of dynamic equipment all kinds of in device to equipment and device carries out consequence
Severe analysis.By the analysis of science, the difference that the judgement of artificial subjectivity is converted into real data is embodied, failure is made
Severity can be more clear and intuitively be distinguished out, provide reliable data base for the analysis of subsequent device reliability
Plinth.So this method for the correct reliable of guarantee refinery device reliability analysis, is of great significance and application value.This is just
It is background and meaning of the invention.
Summary of the invention
It is an object of the invention to be analyzed by the dynamic equipment to the different degrees of typical fault of generation, to obtain this
Influence severity degree of the failure to dynamic equipment itself and to whole device, the risk for improving corresponding dynamic equipment and device are commented
Estimate and maintenance decision, so that the reliability assessment of entire refinery device has more accurate evaluation result and for device and dynamic
Equipment provides more optimized maintenance and maintenance program.
Specific technical solution are as follows:
Typical fault influences the analysis method of consequence on dynamic equipment and device, be used for in refinery device dynamic equipment and
The refinery device is analyzed, and is carried out analysis of severity by consequence caused by the typical fault to dynamic equipment, is somebody's turn to do
The severity degree and different degree of typical fault influence coefficient.
In the analysis method, specifically comprise the following steps:
(1) determine that each influence factor moves equipment to this in the failure of dynamic equipment and this moves the influence grade of equipment place device
Parameter；
(2) device levels, typical fault and the fault degree of dynamic equipment are determined；
According to influence class parameter, determine the typical fault under the fault degree, each influence factor to this move equipment and
The influence class parameter of device where the dynamic equipment；
(3) it will affect class parameter using membership function to be configured to factor ranking matrix and calculating is normalized；
(4) building, consistency check and calculating that the judgment matrix of influence factor is successively carried out with analytic hierarchy process (AHP) are each
The weight of influence factor；
(5) the influence consequence according to the weight of influence factor with fuzzy multi factor evaluation method to influence factor is analyzed；
The sequence severity and different degree for obtaining the failure influence coefficient.
Specifically, the severity degree is divided into 5 grades, is followed successively by from low to high not serious, less serious, general
Seriously, than more serious and very serious.The influence factor includes temperature, pressure, flow, stability and continuity.
Further, influence class parameter corresponding to each influence factor is 5 grades, respectively 1 grade, 2 grades, 3 grades, 4 grades
With 5 grades, wherein 1 grade most light, 5 grades of most serious.
Further, membership function is specially linear distribution membership function.
Specifically, the dynamic equipment is pump, compressor and blower.
In step (4), including as follows step by step:
(4.1) judgment matrix is set as A, the maximum eigenvalue λ of A is calculated by matlab programmax, utilize formula
Carry out coincident indicator calculating, wherein CI is coincident indicator, and n is the order of judgment matrix；
(4.2) random index RI is calculated；
(4.3) CI is compared with RI, obtains test coefficientIf CR < 0.1, then it is assumed that the judgment matrix
It is on the contrary then do not pass through by consistency check；
(4.4) after passing through consistency check, the weight of each factor is calculated using formula (I),
Utilize Matrix Formula ω=[ω1 ω2 ω3 ω4 ω5] Secondary Fuzzy Comprehensive Evaluation is carried out, it obtains shown in formula (II)
Formula,
Using formula (II) as evaluation result formula.
Using this analysis method, by the acquisition and analysis to related data, for different to dynamic equipment all kinds of in device
Influence of the typical fault of degree to equipment and device carries out sequence severity analysis, converts reality for the judgement of artificial subjectivity
Difference in data embodies, and so that the severity of failure is more clear and intuitively is distinguished out, is subsequent device
Fail-safe analysis provides reliable data basis.And then it can be according to the analysis of sequence severity as a result, targetedly arranging
Monitoring, replacement, maintenance or maintenance measure guarantee dynamic equipment safety reliability service.
Detailed description of the invention
Fig. 1 is refinery device reliability analytical technology route map.
Fig. 2 is the subordinating degree function figure that factor index corresponds to each opinion rating.
Abscissa has 5 factor indexs in Fig. 2: I being temperature, II is pressure, III is flow, IV is stability, V is company
Continuous property；Ordinate is degree of membership；5 curves are the functional form for the degree of membership that factor index corresponds to each opinion rating in figure.
Specific embodiment
Below by taking the dynamic equipment of certain Petrochemical Enterprises as an example, and the present invention is described in detail in conjunction with attached drawing and example.
Referring to Fig. 1, data collection arranges first, when using the analysis method in the application in order in evaluation process
In constantly accurate assessment result, need to regather equipment firsthand information data, sequence severity analysis be also required to correlation
Technical staff provides experience grade form, so having devised most commonly used exemplary apparatus pump, compressor in refinery device first
With the various typical fault modes of blower to the influence class parameter table of dynamic equipment and device.On this basis, it can acquire dynamic
Then all kinds of indexs of the reliability of equipment and system carry out FMEA analysis and risk assessment to dynamic equipment, analyze typical case again later
The influence sequence severity that failure generates dynamic equipment and system, finally combines all analyses to formulate corresponding preventative maintenance
Period, overhaul time and maintenance policy complete the reliability assessment that a whole set of device moves device systems.
It is specifically described below:
Determine that each influence factor moves equipment to this in the failure of dynamic equipment and this moves the influence etc. of equipment place device first
Grade parameter.Referring specifically to table 1.
In table 1, the influence factor in the failure of dynamic equipment is determined as 5, respectively temperature, pressure, flow, stabilization
Property, continuity (to equipment and to the influence of device), influencing grade is disposed as 5 grades, respectively 1 grade, 2 grades, 3 grades, 4 grades and 5
Grade, wherein 1 grade is most light, 5 grades of most serious.
The influence class parameter table of comparisons of each influence factor of table 1 to dynamic equipment and device
According to table 1, the various typical faults of pump, compressor and blower are moved with the device where equipment and the dynamic equipment to this
Influence class parameter be determined, and each data are included in table 2, table 3 and table 4 respectively.In table 2, table 3 and table 4, at the same it is right
The device levels of dynamic equipment are determined that in this application, the device levels of dynamic equipment are divided into 3 grades, respectively level-one, two
Grade and three-level.In table 2, table 3 and table 4, the class parameter that influences to dynamic equipment is the influence to the dynamic equipment where typical fault
Class parameter influences class parameter to device for the influence class parameter of the device where the dynamic equipment.
The influence class parameter of various typical fault equipment and device that table 2 pumps
The various typical fault equipment of 3 compressor of table and the influence class parameter of device
The various typical fault equipment of 4 blower of table and the influence class parameter of device
On the basis of ratings above parameter setting, the side that is combined using analytic hierarchy process (AHP) with fuzzy comprehensive evaluation method
Method, the analysis for following the steps below to implement the influence sequence severity that refinery device moves equipment and system determine:
Corresponding membership function building factor ranking matrix is selected according to fuzzy theory and calculating, Zhi Houyun is normalized
The building, consistency check, the calculating of each factor weight that judgment matrix is successively carried out with analytic hierarchy process (AHP), finally according to calculating
Influence consequence of the weight out with fuzzy multi factor evaluation method to each failure factor is analyzed, and obtains influence sequence severity.
As can be seen from Figure 1 the present invention is a very important ring in the analysis of refinery device reliability, with level-one in table 2
For moderate leakage failure in the sealing leak of pump, illustrate the utilization of this evaluation method:
According to table 1 it can be seen that corresponding evaluation of temperature, pressure, flow, stability, this five factor indexs of continuity etc.
Grade is 1-5 grades, chooses most common linear distribution membership function --- and triangular function is as subordinating degree function, factor grade
The functional form of the degree of membership of each factor index is corresponded to as shown in Fig. 2, the failure consequence of different faults is divided into 5 grades, is used
Fuzzy language indicates the severity of failure consequence are as follows: V=it is not serious, it is less seriously, general serious, than more serious, very
Seriously }, wherein V be failure consequence severity, it can be deduced that factor ranking matrix R, and being normalized, as a result such as formula
(1) shown in
The evaluations matrix A1 of the failure are as follows:
Selection weighted mean method is calculated, then the level-one of the moderate leakage failure in the sealing leak of primary pump obscures comprehensive
Close evaluation result R1 are as follows:
Establish judgment matrix A (factor mutually compares two-by-two)
By calculate judgment matrix A maximum eigenvalue λmax=5.0198, it can thus be concluded that the value of coincident indicator CI out
Are as follows:
In formula: λmaxFor the maximum eigenvalue of judgment matrix A, CI is coincident indicator, and n is order of matrix number.Have when 0
There is complete consistency；There is satisfied consistency when CI is close to 0；CI the more makes great difference the more serious, it is seen that CI 0.00495,
With satisfied consistency.In order to measure the size of CI, introduce random index RI, random index RI with sentence
The order of disconnected matrix A is related, and corresponding relationship is as shown in table 5 below:
5 random index RI standard value of table
| n | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
| RI | 0 | 0 | 0.58 | 0.90 | 1.12 | 1.24 | 1.32 | 1.41 | 1.45 | 1.49 |
CI is compared with RI, obtains test coefficientIf 0.1, then it is assumed that the judgment matrix passes through consistent
Property examine, it is on the contrary then do not pass through, be 1.12 by the RI value that table 5 can check in 5 rank matrixes, therefore calculate CR value and with
0.1 compares, as a result as follows:
So judgment matrix A passes through consistency check.
This example is as being consequence size caused by many factors are common, and weighted average type can be realized using the size of weight
The equilibrium of all factors takes into account, therefore selects weighted average type (calculating by multiplication of matrices) here to be calculated, and calculates
Shown in formula such as formula (7).
Then weight is calculated with analytic hierarchy process (AHP), it is necessary first to which each influence factor is compared structure two-by-two
Judgment matrix is made, and judgment matrix has an important properties, i.e.,Scale Method such as table 6 shows.
6 proportion quotiety table of table
Therefore according to 5 kinds of factor Judgement Matricies A.
After passing through consistency check, it is necessary to the weight of each factor is calculated, if judgment matrix
In the formula, a11、a12……annIndicate the fiducial value of each factor, such as a11Indicate temperature/temperature, a12Indicate temperature
Degree/pressure, and so on.
Then each weights omegaiFor calculation formula such as shown in (8), which is the formula (I) in summary of the invention.
Calculate weight matrix ω=[ω1 ω2 ω3 ω4 ω5], it is finally obscured using weight progress second level comprehensive
It closes and judges, evaluation result is formula (9), which is the formula (II) in summary of the invention.
Therefore the weight of each factor is obtained:
ω can similarly be obtained2=0.0989；ω3=0.0989；ω4=0.2744；ω5=0.4289
That is:
ω=[0.0989 0.0989 0.0989 0.2744 0.4289] (11)
Secondary Fuzzy Comprehensive Evaluation, evaluation result are carried out using calculated weight are as follows:
By maximum membership grade principle it can be seen that the maximum value in formula (12) comes the 4th column for 0.2299, with failure consequence
The corresponding sealing for obtaining primary pump of severity V={ not serious, less seriously, general serious, than more serious, very seriously }
The severity degree generated in the case of moderate leakage failure in leakage is than more serious, additionally since failure consequence is also 5
A grade is divided according to ordinate in attached drawing 2, and the corresponding different degree of different failure consequences influences coefficient V ' and is followed successively by from low to high
0.2,0.4,0.6,0.8,1.0, therefore it is 0.8 that the severity of the failure, which influences coefficient,.Other classes are calculated by identical method
Equipment, calculated severity index are easier to confirm whether the equipment is that great hazardous equipment and these failures cause consequence
Severity in a planned way taken corresponding so that enterprise be made targetedly to be handled in face of these failures Shi Nenggeng
The measures such as monitoring, replacement, maintenance, maintenance guarantee that refinery device moves equipment safety reliability service.
Claims (7)
1. typical fault influences the analysis method of consequence on dynamic equipment and device, it is used for the dynamic equipment in refinery device and is somebody's turn to do
Refinery device is analyzed, which is characterized in that analysis of severity is carried out by consequence caused by the typical fault to dynamic equipment,
The severity degree and different degree for obtaining the typical fault influence coefficient.
2. analysis method according to claim 1, which comprises the steps of:
(1) determine that each influence factor joins the influence grade for moving equipment and dynamic equipment place device in the failure of dynamic equipment
Number；
(2) device levels, typical fault and the fault degree of dynamic equipment are determined；
According to class parameter is influenced, the typical fault is determined under the fault degree, each influence factor moves equipment to this and this is dynamic
The influence class parameter of device where equipment；
(3) it will affect class parameter using membership function to be configured to factor ranking matrix and calculating is normalized；
(4) building, consistency check and each influence of calculating of the judgment matrix of influence factor are successively carried out with analytic hierarchy process (AHP)
The weight of factor；
(5) the influence consequence according to the weight of influence factor with fuzzy multi factor evaluation method to influence factor is analyzed；It obtains
The sequence severity and different degree of the failure influence coefficient.
3. analysis method according to claim 1 or 2, which is characterized in that
The severity degree is divided into 5 grades, is followed successively by from low to high not serious, less serious, general serious, relatively tighter
It is heavy and very serious.
4. analysis method according to claim 2, which is characterized in that
The influence factor includes temperature, pressure, flow, stability and continuity.
5. analysis method according to claim 2, which is characterized in that influence class parameter corresponding to each influence factor
It is 5 grades, respectively 1 grade, 2 grades, 3 grades, 4 grades and 5 grades, wherein 1 grade is most light, 5 grades of most serious.
6. analysis method according to claim 2, which is characterized in that membership function is specially linear distribution membership function.
7. analysis method according to claim 1, which is characterized in that the dynamic equipment is pump, compressor and blower.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113378901A (en) * | 2021-05-31 | 2021-09-10 | 国网上海市电力公司 | Active power distribution network expected fault set screening method based on KFCM cluster analysis and PMU device |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103413015A (en) * | 2013-04-24 | 2013-11-27 | 重庆科技学院 | Method for building city gas pipe network vulnerability evaluation model |
| CN106600095A (en) * | 2016-07-27 | 2017-04-26 | 中国特种设备检测研究院 | Reliability-based maintenance evaluation method |
| CN108535433A (en) * | 2018-03-06 | 2018-09-14 | 陈艳粉 | A kind of Water Quality Evaluation system based on wireless sensor network |
| US20190041374A1 (en) * | 2017-08-03 | 2019-02-07 | Central South University Of Forestry And Technology | Rapid screening method of processing raw rice for rice products |
-
2019
- 2019-07-15 CN CN201910634305.0A patent/CN110458408B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103413015A (en) * | 2013-04-24 | 2013-11-27 | 重庆科技学院 | Method for building city gas pipe network vulnerability evaluation model |
| CN106600095A (en) * | 2016-07-27 | 2017-04-26 | 中国特种设备检测研究院 | Reliability-based maintenance evaluation method |
| US20190041374A1 (en) * | 2017-08-03 | 2019-02-07 | Central South University Of Forestry And Technology | Rapid screening method of processing raw rice for rice products |
| CN108535433A (en) * | 2018-03-06 | 2018-09-14 | 陈艳粉 | A kind of Water Quality Evaluation system based on wireless sensor network |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113378901A (en) * | 2021-05-31 | 2021-09-10 | 国网上海市电力公司 | Active power distribution network expected fault set screening method based on KFCM cluster analysis and PMU device |
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